Multi-level transcriptome sequencing identifies COL1A1 as a candidate marker in human heart failure progression

作者：Xiumeng Hua, Yin‐Ying Wang, Peilin Jia, Qing Xiong, Yiqing Hu, Yuan Chang, Songqing Lai, Yong Xu, Zhongming Zhao, Jiangping Song · 发表于：BMC Medicine · 年份：2020 · DOI：10.1186/s12916-019-1469-4 · 被引用次数：122 · 研究领域：Cardiac Fibrosis and Remodeling、GDF15 and Related Biomarkers、Ferroptosis and cancer prognosis

Abstract Background Heart failure (HF) has been recognized as a global pandemic with a high rate of hospitalization, morbidity, and mortality. Although numerous advances have been made, its representative molecular signatures remain largely unknown, especially the role of genes in HF progression. The aim of the present prospective follow-up study was to reveal potential biomarkers associated with the progression of heart failure. Methods We generated multi-level transcriptomic data from a cohort of left ventricular heart tissue collected from 21 HF patients and 9 healthy donors. By using Masson staining to calculate the fibrosis percentage for each sample, we applied lasso regression model to identify the genes associated with fibrosis as well as progression. The genes were further validated by immunohistochemistry (IHC) staining in the same cohort and qRT-PCR using another independent cohort (20 HF and 9 healthy donors). Enzyme-linked immunosorbent assay (ELISA) was used to measure the plasma level in a validation cohort (139 HF patients) for predicting HF progression. Results Based on the multi-level transcriptomic data, we examined differentially expressed genes [mRNAs, microRNAs, and long non-coding RNAs (lncRNAs)] in the study cohort. The follow-up functional annotation and regulatory network analyses revealed their potential roles in regulating extracellular matrix. We further identified several genes that were associated with fibrosis. By using the survival time before...